Slashed generalized exponential distribution

In this paper, we introduce an extension of the generalized exponential (GE) distribution, making it more robust against possible influential observations. The new model is defined as the quotient between a GE random variable and a beta-distributed random variable with one unknown parameter. The resulting distribution is a distribution with greater kurtosis than the GE distribution. Probability properties of the distribution such as moments and asymmetry and kurtosis are studied. Likewise, statistical properties are investigated using the method of moments and the maximum likelihood approach. Two real data analyses are reported illustrating better performance of the new model over the GE model.     

The determinacy of the regression factor score predictor based on continuous parameter estimates from categorical variables

The estimation of population parameters of the continuous common factor model from categorical observed variables is meanwhile regularly performed. It is shown that the formula for the calculation of the determinacy of the regression factor score predictor from the estimated model parameters has to be adapted under these conditions. A method for the calculation of this determinacy from the model parameters of the continuous population factor model based on categorical variables is proposed and evaluated by means of simulated population data. It turns out that using the uncorrected formula can lead to serious overestimation of determinacy for categorical variables.     

Slashed generalized Rayleigh distribution

We introduce a new family of distributions suitable for fitting positive data sets with high kurtosis which is called the Slashed Generalized Rayleigh Distribution. This distribution arises as the quotient of two independent random variables, one being a generalized Rayleigh distribution in the numerator and the other a power of the uniform distribution in the denominator. We present properties and carry out estimation of the model parameters by moment and maximum likelihood (ML) methods. Finally, we conduct a small simulation study to evaluate the performance of ML estimators and analyze real data sets to illustrate the usefulness of the new model.     

Mixture inverse Gaussian for unobserved heterogeneity in the autoregressive conditional duration model

In this paper, we assume that the duration of a process has two different intrinsic components or phases which are independent. The first is the time it takes for a trade to be initiated in the market (for example, the time during which agents obtain knowledge about the market in which they are operating and accumulate information, which is coherent with Brownian motion) and the second is the subsequent time required for the trade to develop into a complete duration. Of course, if the first time is zero then the trade is initiated immediately and no initial knowledge is required. If we assume a specific compound Bernoulli distribution for the first time and an inverse Gaussian distribution for the second, the resulting convolution model has a mixture of an inverse Gaussian distribution with its reciprocal, which allows us to specify and test the unobserved heterogeneity in the autoregressive conditional duration (ACD) model.

Our proposals make it possible not only to capture various density shapes of the durations but also easily to accommodate the behaviour of the tail of the distribution and the non monotonic hazard function. The proposed model is easy to fit and characterizes the behaviour of the conditional durations reasonably well in terms of statistical criteria based on point and density forecasts.     

Multivariate log-Birnbaum–Saunders regression models

In this paper, we present a multivariate version of the skewed log-Birnbaum–Saunders regression model. This new family of distributions holds good properties such as marginal variables following univariate skewed log-Birnbaum–Saunders distributions, besides presenting the usual log-Birnbaum–Saunders distribution as a particular case. Furthermore, the model parameters are estimated through maximum-likelihood methods, a closed-form expression for the Fisher’s information matrix is presented, and testing hypothesis for model parameters is performed. Two real datasets are analyzed and results are discussed.     

Adaptation of the short version of the Psychological Capital Questionnaire (PCQ-12) into Spanish / Adaptación al español de la versión reducida del Cuestionario de Capital Psicológico (PCQ-12)

Psychological capital (PsyCap) has been a topic of increasing interest in the last decade. However, there is a lack of validated instruments in Spanish to map PsyCap and its consequences for individuals’ well-being. Consequently, the goal of this study is to adapt the 12-item short version of the Psychological Capital Questionnaire (PCQ-12) to the Spanish context by analysing its internal consistency and reliability, factor solution and external validity. Results indicated that the PCQ-12 exhibited good Cronbach’s alpha (.87) and omega coefficient (.93) values in a sample from a vehicle inspection company (n = 798). As expected, results also revealed that a second-order factor structure provided the best fit. Moreover, PsyCap is associated with increased job engagement (β = .579; R²_adjusted = .333), decreased job burnout (β = ?.409; R²_adjusted = .166), and lower psychological distress (β = ?.349; R²_adjusted = .121) (all p < .01), which provided additional support for using the PCQ-12 in the Spanish context. Implications for theory and practice are discussed.     

Promoting healthy transition to college through mindfulness training with first-year college students: Pilot randomized controlled trial

Objective: Given the importance of developmental transitions on young adults' lives and the high rates of mental health issues among U.S. college students, first-year college students can be particularly vulnerable to stress and adversity. This pilot study evaluated the effectiveness and feasibility of mindfulness training aiming to promote first-year college students' health and wellbeing. Participants: 109 freshmen were recruited from residential halls (50% Caucasian, 66% female). Data collection was completed in November 2014. Methods: A randomized control trial was conducted utilizing the Learning to BREATHE (L2B) program, a universal mindfulness program adapted to match the developmental tasks of college transition. Results: Participation in the pilot intervention was associated with significant increase in students' life satisfaction, and significant decrease in depression and anxiety. Marginally significant decrease was found for sleep issues and alcohol consequences. Conclusions: Mindfulness-based programs may be an effective strategy to enhance a healthy transition into college.     

Violence against women in Spain and Cuba: The same reality,two different visions / Violencia hacia la mujer en España y Cuba: una misma realidad,dos visiones diferentes

This study aims to analyse the acceptance of gender violence in Spanish and Cuban populations. We analysed the influence of sexist beliefs and other ideologies that justify unequal gender relationships. A total of 230 men and women from Spain and 200 from Cuba participated by answering a questionnaire. The results showed the effect of participants’ gender and nationality as well as ideological variables (sexism, beliefs in a just world and codes of honour) that legitimise the status quo of gender violence. The male participants and the Cuban participants accepted violence against women more than the female participants and the Spanish participants. What is more, the results showed a pattern in the influence of the ideological variables that differed depending on the participants’ nationality. In Spain, the relationship between participants’ benevolent sexism and the justification of violence was mediated by codes of honour. In Cuba, the relationship between hostile sexism and acceptance of violence against women was mediated by beliefs in a just world.     

Influential factors in the choice of public transportation or cars as the mode of transportation in habitual commutes / Factores que influyen en la elección del transporte público o el automóvil como modo de transporte en los desplazamientos habituales

The goal of this study is to analyse the differences in attitudes towards habitual modes of transportation among users of public and private transportation. The explanatory capacity of attitudes when determining the mode choice, along with the structural and sociodemographic factors, are also verified. The study was performed in three Spanish cities with 742 participants. The results revealed that cars are better rated than public modes of transportation in the attributes associated with immediate advantages (i.e., speed and availability) and convenience. Subways are highly rated in both immediate and deferred advantages (environment, safety, cost and health). Buses are the mode rated the lowest of the three. Using logistic regression, it was verified that the variance explained by a model that includes attitudes (R² = .639) is higher than the variance explained by a model based solely on variables related to infrastructures (R² = .489). The discussion of these results includes proposals aimed at decreasing car use.